Machine Translation (MT) systems are increasingly being used in various business processes for breaking the language barrier. In scenarios where hard-copies of documents need to be translated automatically, the MT systems can be used after the documents are processed by an OCR. The output of the OCR might be noisy. The noise refers to various possible errors such as, but not restricted to, character replacement or segmentation errors. In case of a character replacement error, a character in an image is wrongly recognized as a different character or a sequence of characters. In case of segmentation errors, either a space between two words is not recognized or one or more extra spaces are inserted in the middle of a word. Such noisy output may result in faulty translation by the MT system. Further, correcting such errors manually takes considerable time and effort.